Optimization Approach for Detecting the Critical Data on a Database

dc.creatorAlluvada, Prashanth
dc.date2008-04-20
dc.date2008-04-27
dc.date.accessioned2026-07-07T09:35:09Z
dc.date.available2026-07-07T09:35:09Z
dc.descriptionThrough purposeful introduction of malicious transactions (tracking transactions) into randomly select nodes of a (database) graph, soiled and clean segments are identified. Soiled and clean measures corresponding those segments are then computed. These measures are used to repose the problem of critical database elements detection as an optimization problem over the graph. This method is universally applicable over a large class of graphs (including directed, weighted, disconnected, cyclic) that occur in several contexts of databases. A generalization argument is presented which extends the critical data problem to abstract settings.
dc.description6 pages, 1 figure, 3 tables. corrected typos, added remarks
dc.identifierhttps://arxiv.org/abs/0804.3171
dc.identifierhttp://arxiv.org/abs/0804.3171
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/159740
dc.subjectDatabases
dc.titleOptimization Approach for Detecting the Critical Data on a Database
dc.typetext

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